欧亚国际

来自欧洲的科学家刚刚在食品领域期刊Foods上发表了题为Detection of Meat Adulteration Using Spectroscopy-Based Sensors的文章，着重介绍了多光谱成像技术在肉品造假检测中的应用。 

该设备在肉品研究部分应用领域以及所发表文章如下：

肌肉、脂肪和肉色文章-Comparison of a multispectral vision system and a colorimeter for the assessment of meat color

肌肉、脂肪分布文章-Spectral imaging for monitoring structure and colour development of dry fermented sausages

肉变质研究文章-Exploiting multispectral imaging for non-invasive contamination assessment and mapping of meat samples

香肠发酵文章-Spectral imaging for monitoring structure and colour development of dry fermented sausages

发酵香肠颜色形成文章-Colour formation in fermented sausages by meat-associated staphylococci with different nitrite- and nitrate-reductase activities

原料肉牛肉掺假（猪肉）文章-Multispectral image analysis approach to detect adulteration of beef and pork in raw meats

肉持续干燥品质检测文章-New vision technology for multidimensional quality monitoring of continuous frying of meat

牛肉掺假（马肉）检测文章-Multispectral imaging (MSI): A promising method for the detection of minced beef adulteration with horsemeat

冷冻解冻肉快速检测文章-Rapid detection of frozen-then-thawed minced beef using multispectral imaging and Fourier transform infrared spectroscopy

猪肉中铁卟啉含量快速、无损检测-Rapid and Non-destructive Detection of Iron Porphyrin Content in Pork Using Multispectral Imaging Approach

肉品掺假多光谱检测-Detection of Meat Adulteration Using Spectroscopy-Based Sensors 

Detection of Meat Adulteration Using Spectroscopy-Based Sensors

1.byLemonia-Christina Fengou, *,Alexandra Lianou2,*,Panagiοtis Tsakanikas1,Fady Mohareb 3 andGeorge-John E. Nychas

1Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, 11855 Athens, Greece

2. Division of Genetics, Cell Biology and Development, Department of Biology, University of Patras, 26504 Patras, Greece

3. Bioinformatics Group, Department of Agrifood, School of Water, Energy and Environment Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL, UK

Foods 2021, 10(4), 861; http://doi.org/10.3390/foods10040861

Abstract

Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evalsuated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific.

Keywords: adulteration;minced meat;multispectral imaging;sensors;spectroscopy